FMODB: The World's First Database of Quantum Mechanical Calculations for Biomacromolecules Based on the Fragment Molecular Orbital Method. - Daisuke Takaya; Chiduru Watanabe; Shunpei Nagase; Kikuko Kamisaka; Yoshio Okiyama; Hirotomo Moriwaki; Hitomi Yuki; Tomohiro Sato; Noriyuki Kurita; Yoichiro Yagi; Tatsuya Takagi; Norihito Kawashita; et al. (J. Chem. Inf. Model., 2021)

Protein-ligand binding affinity prediction of cyclin-dependent kinase-2 inhibitors by dynamically averaged fragment molecular orbital-based interaction energy. - Kenichiro Takaba; Chiduru Watanabe; Atsushi Tokuhisa; Yoshinobu Akinaga; Biao Ma; Ryo Kanada; Mitsugu Araki; Yasushi Okuno; Yusuke Kawashima; Hirotomo Moriwaki; Norihito Kawashita; Teruki Honma; et al. (J. Comput. Chem., 2022)

EspalomaCharge: Machine learning-enabled ultra-fast partial charge assignment. - Yuanqing Wang; Iván Pulido; Kenichiro Takaba; Benjamin Kaminow; Jenke Scheen; Lily Wang; John D. Chodera (CoRR, 2023)

Espaloma-0.3.0: Machine-learned molecular mechanics force field for the simulation of protein-ligand systems and beyond. - Kenichiro Takaba; Iván Pulido; Mike Henry; Hugo MacDermott-Opeskin; John D. Chodera; Yuanqing Wang (CoRR, 2023)

On the design space between molecular mechanics and machine learning force fields. - Yuanqing Wang; Kenichiro Takaba; Michael S. Chen; Marcus Wieder; Yuzhi Xu; Tong Zhu; John Z. H. Zhang; Arnav Nagle; Kuang Yu; Xinyan Wang; Daniel J. Cole; Joshua A. Rackers; et al. (CoRR, 2024)